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Mendeley readers
| Chapter title |
Clustering.
|
|---|---|
| Chapter number | 19 |
| Book title |
Bioinformatics
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6613-4_19 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6611-0, 978-1-4939-6613-4
|
| Authors |
G. J. McLachlan, R. W. Bean, S. K. Ng |
| Editors |
Jonathan M. Keith |
| Abstract |
Clustering techniques are used to arrange genes in some natural way, that is, to organize genes into groups or clusters with similar behavior across relevant tissue samples (or cell lines). These techniques can also be applied to tissues rather than genes. Methods such as hierarchical agglomerative clustering, k-means clustering, the self-organizing map, and model-based methods have been used. Here we focus on mixtures of normals to provide a model-based clustering of tissue samples (gene signatures) and of gene profiles, including time-course gene expression data. |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Pakistan | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 24% |
| Student > Master | 4 | 16% |
| Researcher | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Professor > Associate Professor | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 6 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 20% |
| Biochemistry, Genetics and Molecular Biology | 4 | 16% |
| Medicine and Dentistry | 3 | 12% |
| Engineering | 2 | 8% |
| Business, Management and Accounting | 1 | 4% |
| Other | 4 | 16% |
| Unknown | 6 | 24% |